Testing the Equality of Multi-VariancesThe equality of variances across populations is called homogeneity of variances or homoscedasticity. Some statistical tests, such as testing equality of the means by the t-test and ANOVA, assume that the data come from populations that have the same variance, even if the test rejects the null hypothesis of equality of population means. If this condition of homogeneity of variance is not met, the statistical test results may not be valid. Heteroscedasticity refers to lack of homogeneity of variances. Bartlett's Testis used to test if k samples have equal variances. It compares the Geometric Meanof the group variances to the arithmetic mean; therefore, it is a Chi-square statistic with (k-1) degrees of freedom, where k is the number of categories in the independent variable. The test is sensitive to departures from normality. The sample sizes do not have to be equal but each must be at least 6.

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